This column will continue the discussion of the practicalities and pitfalls of quantitative spectroscopy started in the last column (1). The reason that a discussion of quantitative spectroscopy matters for cannabis analysis is that many cannabis potency methods use high performance liquid chromatography (HPLC) along with ultraviolet-visible (UV-vis) spectroscopic detection (2). Also, there exist cannabis potency analyzers based on mid-infrared spectroscopy (3). The fundamental equation of quantitative spectroscopy is Beer’s Law (4), whose form is seen in Equation 1.

where A is the absorbance; ε is the absorptivity, a fundamental physical constant of a molecule; L is the pathlength or sample thickness; and C is the concentration.

I will dispense with any further discussion of Beer’s Law or the basics of quantitative spectroscopy and refer you to my previous columns on these topics (1,5–7). In this installment, we discuss how to measure absorbances properly, and compare the use of peak heights and peak areas in creating calibrations.

In the spectroscopic literature, and in our discussion of quantitative spectroscopy so far (1,5–7), much ink has been spilled about determining the absorptivity because this is often the unknown quantity we need to determine to finalize a calibration. We have also discussed the importance of measuring concentrations properly (1,5–7). Pathlengths, L, are generally known or fixed so they are typically not a problem. That leaves the final parameter in Beer’s Law: absorbance. To review, we measure the absorbance of standard samples of known concentration to achieve calibrations. What then is the best way to measure this important property?

A tried-and-true way to measure absorbance is the height of a peak in a spectrum (4). The first thing to do in measuring absorbances is to determine which peak to use in your analyte’s spectrum. This is a problem because samples may contain molecules whose peaks can overlap with and interfere with the measurement of the absorbance of the peaks from your analyte. That is, we need to measure the height of a peak that is spectrally isolated and overlaps as little as possible with peaks from any other components in a sample (4). To find a spectrally isolated peak, the first thing to do is consult spectra of the pure materials that make up your sample mixture. This is illustrated in 

The four spectra in Figure 1 are of the pure materials isopropanol (IPA), ethanol (EtOH), acetone, and water. Imagine we want to measure the concentration of IPA in a mixture of these four substances. Which peak should we use? An examination of the spectra, seen in Figure 1, shows the IPA peak at 948 cm

, which is marked in the figure, is mostly clear of interference from peaks of the other molecules in the mixture. If you look closely in Figure 1, you can see the start of a water peak at 948 cm

, and I discuss how to deal with this later.

Interferent peaks are a fundamental problem with the single peak quantitative method I have been discussing in the pages of this magazine (1,5–7). In the past, this problem limited the use of quantitative spectroscopy (4). Fortunately, with the advent of computers and powerful algorithms accurate concentration determinations using spectroscopy can be made on complex mixtures (4) including hemp and cannabis, cannabis extracts, cannabis distillates, and tinctures (8–13). Alas, a discussion of these algorithms is beyond the scope of this column series. For HPLC analyses using spectroscopic detection, interferent peaks are generally not a problem because the chromatograph breaks the mixture down into its pure components (2).

The next thing to do to insure proper absorbance measurements is to make up your standard samples, measure their spectra, and then overlay them as shown in 

This is done to insure the size of the analyte peak of interest changes with concentration. Note in Figure 2 that our IPA peak at 948 cm

 does change in peak size with concentration, so we can go ahead and use it in our calibration.

 peak in one of the standard spectra is seen in 

Note that this peak leans to the left, and has a baseline elevated above zero absorbance. It would be tempting to just place your cursor at the top of this peak and measure the absorbance there, but since there is a weak water interference here you would obtain an incorrect absorbance. How do we measure the peak height of such a thing?

The first thing to realize is that when a computer displays a spectrum there is not an absorbance measurement at every possible wavenumber, but there are absorbance values at specific wavenumber values. This is seen in 

 where the red x’s represent the actual absorbance measurements that make up our IPA peak of interest seen in Figure 3.

Instinctively, we tend to want to measure the peak height at its top, but why? Absorbances at other wavenumbers in this peak also change value with analyte concentration as seen in Figure 2. Why don’t we measure our absorbance value at these alternate wavenumbers? Recall our discussion of signal-to-noise ratio (SNR) in a previous column (1), that the SNR for a peak is its peak height divided by the noise level in that spectral vicinity. For a given peak the signal is greatest at the top of the peak, hence measuring peak height at its top will give an absorbance measurement with the best SNR.

How do we deal with our left-leaning peak with an elevated baseline, which can be seen in Figure 3? By the way, non-zero baselines can be caused by instrumental problems or interference from other molecules. Rather than reading the raw peak height, we almost always measure the peak height with respect to a baseline. In Figure 3, the baseline endpoints and baseline are shown in blue. The purpose of the baseline is two-fold. First, by measuring the peak height with respect to the baseline the water contribution to the peak at 948 cm

 in Figure 3 is eliminated because its contribution falls under the baseline. Second, for a peak like the one in Figure 3 that leans left or right, measuring with respect to a baseline makes sure that only this peak itself and not adjacent portions of the spectrum are used.

The tricky part in this process is establishing the baseline endpoints; that is, at what wavenumbers to locate the beginning and end of the baseline. In Figure 3 the left baseline endpoint is at 968 cm

, and the right baseline endpoint is at 925 cm

. Note that the baseline endpoints correspond to the peak edges. How did I choose these? There do exist software programs that can pick peak edges and baseline endpoints, but in my experience a human being—the thing with a brain and eyeballs—can do better. Almost all spectroscopy or chromatography software programs will allow you to visualize a peak and set the baseline endpoints manually. It does take a little training and user interaction to do this properly, but I prefer it to trusting the computer to do things for me. Basically, you should choose baseline endpoints where the peak flattens out and is parallel to the baseline. As it turns out, the height of our peak of interest, the distance between the baseline and the top of the peak at 948 cm

 represented by the green line in Figure 3, is 0.09 absorbance units. This is the number we would use as part of a Beer’s Law plot to obtain a calibration (5–7).

Some spectroscopic quantitative methods use peak height, others use peak area. We know how peak heights are measured, how are peak areas calculated? It begins the same as measuring a peak height, drawing a correct baseline as seen in Figure 3 above. Now, look at Figure 4. There are 12 wavenumbers with absorbance values between 968 and 925 cm

. To calculate a peak area for this peak the absorbance at each of these wavenumbers is calculated with respect to the baseline shown in Figure 3, and then these dozen absorbances are added together. Thus, for the peak shown in Figure 3 the area is 1.49 absorbance units using the baseline shown in blue. Note that the peak area value is much greater than the peak height value because the peak height is a single absorbance measurement, whereas in this case the peak area is the sum of 12 absorbance measurements.

Now that we know how peak heights and areas are measured, which one should you use in your calibration? This is actually a complex question and has been a topic of debate in the literature (4). In my last column (1), we discussed that the SNR of a spectrum is a measure of spectral quality, and that it can be calculated by taking an absorbance value and dividing by the noise level. This means that both peak heights and peak areas can be used to calculate a SNR. Which measurement then gives us the best signal-to-noise ratio? For the peak seen in Figure 3, the noise level at a point in the baseline near the peak is 0.0106 absorbance units. 

 shows the results of SNR calculations using this noise value and the peak height and area results discussed above.

Note that the peak area SNR is 140, whereas the peak height SNR is 8.5, a difference of 16.5 times. This is because the peak area value is much greater than the peak height value and in both cases the denominator was the same. Thus, we can conclude that peak areas have better SNRs than peak heights and thus will in general produce more accurate calibrations.

Another reason to use peak areas is less mathematical. By using peak height, which again is a single absorbance measurement, you are literally putting all your eggs in one basket. If for any reason anything is off about this one absorbance measurement, such as variation in interferent absorbances or a noise spike, the accuracy of your entire measurement is shot. Whereas with peak area, if one absorbance is wrong it is averaged out over the other absorbances that comprise the peak, meaning an inaccuracy in one measurement has less effect on the overall measurement than with peak heights. This ability to tolerate an inaccurate measurement and still maintain accuracy is called 

, a measure of calibration quality that I hope to discuss more in a future column. In our case here it is safe to say that peak area calibrations are more robust than peak height calibrations.

In my opinion, peak areas are better than peak heights for quantitative spectroscopic analyses. However, there do exist examples in the literature where peak height calibrations give better results than peak area. Given this fact my approach to this issue is simple. Try peak area first, and if you run into problems, then try peak height. At the end of the day the samples themselves will determine which route is best.

Since absorbance is one of the parameters in Beer’s Law, it is important to measure it properly. For single peak quantitative methods, the first thing to do is to consult spectra of the pure components in your sample. You will need to pick an analyte peak as free from interference as possible. The next thing to do is look at the spectra of your standards to ensure that your analyte peak varies with analyte concentration. You then need to draw a baseline under your peak, being careful to choose proper baseline endpoints. Then, you need to measure the peak height or area and use it in your calibration. In this author’s opinion, peak area is better because its calibrations have a better signal-to-noise ratio and are more robust than peak height calibrations. However, since on occasion peak height calibrations can be better, the safest route is to try peak area first, and if the accuracy obtained is not sufficient then try peak height.

M.W. Giese, M.A. Lewis, L. Giese, and K.M. Smith, 

Quantitative Spectroscopy: Theory and Practice

 (Elsevier, Boston, Massachusetts, 2002).

B.C. Smith, M. Lewis, and J. Mendez, “Optimization of Cannabis Grows Using Fourier Transform Mid-Infrared Spectroscopy,” PerkinElmer Application Note (2016).

B.C. Smith, C. Fucetola, K. Erhmantraut, and 

, PhD, is Founder, CEO, and Chief Technical Officer of Big Sur Scientific. He is the inventor of the BSS series of patented mid-infrared based cannabis analyzers. Dr. Smith has done pioneering research and published numerous peer-reviewed papers on the application of mid-infrared spectroscopy to cannabis analysis, and sits on the editorial board of 

®. He has worked as a laboratory director for a cannabis extractor, as an analytical chemist for Waters Associates and PerkinElmer, and as an analytical instrument salesperson. He has more than 30 years of experience in chemical analysis and has written three books on the subject. Dr. Smith earned his PhD on physical chemistry from Dartmouth College.
Direct correspondence to: 

Articles

Cannabis Analysis 

Part II of this series discusses how to measure absorbances properly, and compares the use of peak heights and peak areas in creating calibrations.

Quantitative Spectroscopy: Practicalities and Pitfalls, Part II

Advancement in extraction technology, blossoming product innovation, and state legalization continues to expand in the cannabis and hemp industry. With all that, there has been an ever evolving and growing list of concentrate product types. In this article, the various extract types will be defined so there can be some consensus once and for all.

The cannabis industry is still relatively young, but that has not stunted the development of innovative extraction technologies and cannabis product types. In hyper-competitive markets—such as California, Colorado, and Washington—manufacturers are competing on price or novelty. While most consumers favor low prices, as in any industry, there is a strong and growing market for super premium novelty products. This is especially prevalent in the concentrates category.

As covered in the solventless extracts overview in March (1), cannabis concentrates have historically been available for a long time. The first method of producing concentrates was hash production, where trichomes are separated from the plant and collected. Now, there are many more methods of extraction which produce many different extract types. Each extract type has a different viscosity, color, flavor profile, and can even have a different chemical composition. These differences are based on the extraction solvent, extraction method, source material, and other factors. Below is a list of extraction methods and extraction solvents that are commonly used in the cannabis industry today.

: mechanical separation of the trichomes from the cannabis flower using sieves of specific mesh size.

: mechanical extraction method, also known as expression, where plant material is pressed to extract and collected the resin from the plant material.

: extraction by diffusion where ground plant material is soaked with organic solvent to extract desirable compounds.

: a solvent is heated to reflux, then the solvent vapor soaks the solid material then condenses as a mixture of desired compounds and solvent. The solvent is later evaporated to leave behind the extracted compounds.

: desired compounds are extracted by introducing the pressurized fluid to the solid matrix, where, as a supercritical fluid (SCF), the desired compounds are soluble. The SCF, usually CO

, is then converted to a gas and evaporated from the solution leaving just the desired compounds.

Extraction methods and solvent types produce relatively different outcomes, especially with respect to the viscosity of the extract. Each process extracts a different matrix of compounds as a result of solvent polarity, solvent density, quality of plant material, and others. Solvent extraction can be done using polar solvents (such as ethanol), or nonpolar solvents (like CO

 and butane). Ethanol is an incredibly efficient solvent and easily extracts both tetrahydrocannabinol (THC) and tetrahydrocannabinolic acid (THCA) at a wide range of temperatures. Most cannabinoids and terpenes, such as THC or limonene, are nonpolar. Hydrocarbon solvents and CO

 are both nonpolar, so they make excellent choices for extraction solvents. However, THCA is polar and, therefore, less soluble in nonpolar solvents than THC.

The viscosity of cannabis extract is an effect of the concentration of terpenes, cannabinoids, waxes, and other compounds that individually have a wide range of viscosities. At room temperature, atmospheric pressure, and in its pure form:

Terpenes are a volatile liquid and many of them act as solvents. So, an extract with a relatively high concentration of terpenes will be a liquid. If an extract has a high concentration of THCA, the extract will likely be a solid or have crystalline formations in the extract. If there is a high concentration of plant waxes, the extract will likely be a solid or have a very high viscosity.

The cannabis plant naturally produces THCA. However, during the drying and curing or if cannabis ages without proper storage, some of the THCA can turn into THC. Terpenes will also change during the drying and curing process because of oxidation, evaporation, and the plant’s enzymes continuing to react and produce different terpenes. So, a freshly harvested cannabis flower will have a different chemical profile than that same flower after it has been dried and cured. In the past few years, many operators have produced cannabis extract using freshly harvested cannabis flower to create an extract with a very different chemical profile. After harvest, the cannabis flower is quickly packed and frozen to preserve its chemical profile and trichome structure. The result is 

, an extract with a terpene and cannabinoid profile of the freshly harvested cannabis flower. Live resin can be produced with many different extraction methods, but it is most commonly produced through hydrocarbon extraction and ice water hash.

Ice water hash is a method intended to physically separate the trichomes from the cannabis flower by suspending and then agitating the cannabis flower in a bath of ice and water. The interaction with the ice, physically knocks the trichomes off of the cannabis flower and they end up in the cold water. The mix of water, ice, cannabis flower, and trichomes is then filtered through mesh screens or bags with progressively smaller pore sizes until all trichomes have been collected. These trichomes are collectively called hash and can be further processed in many ways to produce extracts of different compositions and viscosities.

In summary, different types of extracts come from different extraction methods, source cannabis material, and any further processing that is done after the extraction. There is no governing body to standardize nomenclature around methods or extract types. Innovation in cannabis extraction technology, extract refinement, and method of administration spaces are all continuing to happen at a fast pace. Until there is official authority around naming conventions, leaders in the cannabis industry are taking responsibility for standardizing language around the wide variety of products that are on the market today.

Some common terms and definitions include:

: General term for concentrated cannabis resin, usually packaged in a jar.

: A collection of trichomes produced through physical separation. Hash can look like sand, a puck, or amorphous solid.

: Cannabis concentrate that is primarily made up of THCA crystalline that has been heated, poured on a flat surface, cooled, and undisturbed to form a glass-like structure. This cannabis concentrate will “shatter” like glass.

: A cannabis concentrate with a ratio of terpenes, THC, and THCA that produces a consistency like clumped sugar.

: Cannabis extract with a very high concentration of terpenes, creating a very liquid or saucy consistency.

: Cannabis extract high in terpenes and THC. It is whipped, which results in a fluffy, whipped consistency.

: Cannabis extract high in cannabinoids, has some plant waxes, and relatively low in terpene concentration. This yields a thick, waxy consistency.

: Cannabis extract produced from freshly harvested and frozen cannabis plant material.

: Extract produced from pressing hash that was made from freshly harvested and frozen plant material.

https://www.cannabissciencetech.com/view/solventless-extracts-an-overview

 is the founder, CEO, and Chief Extractor of Heylo. With a background in chemistry and clinical research, Lo was inspired to explore cannabis as a medicine and to enter the emerging industry. She joined Eden Labs, a leading CO

 extraction equipment manufacturer to support and expand a Research and Development department. There she managed the development of their latest and greatest CO

 extraction system. In 2017, after working with Eden Labs and another cannabis processor, Lo launched Heylo with a mission to help people get more out of life with cannabis.

Extraction Science

The various extract types are defined so there can be some consensus once and for all.

Concentrate...What Do You Call It?

Controlled agriculture facilities are unique and have generally higher power demands than what a utility may be used to seeing. It is important to understand the power that your facility’s process requires as it drives your utility rate structure and your power costs. Navigating and evaluating alternative energy options can help reduce your rates and improve your overall emissions impact and environmental, social, and governance (ESG) performance. Evaluating initial system costs and production of all power options and combinations are key to determining the best solution. Your power rates, grid capacity, and timing can make or break the viability of a new location or upgrade of an existing facility. A firm understanding of how you plan to use your facility, what power options are available, and strong partners to guide you to the best solution are critical to your bottom line.

Whether new construction or retrofit, understanding how your facility runs is critical. The process that your facility uses to produce its yield involves many steps. Each of those steps has a power need. Water pumps require power and operate at a rate based on your facility. Your plants require temperature and humidity levels that must be maintained. Your heating, ventilation, and air conditioning (HVAC) system is reacting to these set points and working to keep your system in balance. Lighting levels must be maintained at specific thresholds. It is well worth the time to think through your current process, your future plans for refinement or increased production, or goals for a new or enhanced facility.

Modeling the operations outlined above can be extensive. The equipment and processes all interrelate and react to growth and harvest schedules, solar gain, temperature, humidity, and many other factors. This interrelation requires that you view your facility’s needs on an hourly basis in what is called an 8760 load profile. This profile summarizes the complexity of how your facility behaves and communicates information to relevant parties. The 8760 is a blend of electrical and mechanical engineering, process design, energy modeling, solar evaluation, and equipment performance. Having the right partners with the experience and capability to perform this analysis properly is a critical step in finding your optimal power solution. As a designer and builder, ARCO/Murray Power Solutions (AMPS) develops these profiles in-house with their multidiscipline engineering team (see 

While developing an 8760 is a sophisticated process, it is still a model approximating your needs. Backfilling this with performance data will yield a more refined prediction. Monitoring systems can be integrated into new or existing construction to empower your process with real-time information of how your facility functions.

Investigating your local grid and its potential strengths and weaknesses will set your project up for success. Communicate your energy needs with the utility company early so that you can plan for the timing of possible infrastructure upgrades or even consider alternative sites if building a new facility.

Work to understand the resiliency and quality of the local grid and any special considerations for your location. It is important to understand the power that you will receive because bad power quality can damage equipment. Prepare for potential outages by knowing common regional causes and seasonality. In larger outage events, the downtime difference could be days if your location is on the same distribution line as an essential service. These outages will drive your backup needs and you must account for the necessary infrastructure to keep operating when grid power may be down.

As a conscientious cultivator, you want to understand the emissions impact of your facility and product. While using power from the grid may look the same on the surface, there are significant differences in emissions impact between a grid with clean energy sources and dirty ones. Understanding the energy makeup of your local grid and its source of power is vital for ESG reporting, which has impacts in both consumer and investor spaces. Investigate your available electric suppliers and consider green sourcing opportunities, as well (see 

Utility rates are not constant and can have large fluctuations in prices, especially related to peak demand. Each utility is different in their rate structure. Your peak usage defines your rate group, which sets your rate structure. Applying the rate structure to the 8760 will result in an accurate estimate of your electrical bill and will be a great start for exploring energy procurement options (see 

Your local utility is not the only source of power available to you. By using alternative sources, you can reduce your carbon footprint and improve ESG performance. It can also mean energy independence, reduced risk of future grid utility escalations, and resiliency and consistency of supply that may not be available through your local grid. If grid power needs at your facility requires utility infrastructure upgrades that could have long lead times and construction durations, on-site alternative power options will be valuable
to consider.

These on-site systems are typically in the form of:

Navigating through the appropriate size and potential combination of multiple sources requires expert guidance. Alternative source production is overlaid atop the 8760 to help understand the impacts and benefits to you. In some cases, there are additions or reductions to your facility’s infrastructure with the implementation of an alternative source that needs to be understood and accounted for. Additionally, with today’s supply chain volatility, understanding equipment availability, lead times, and current pricing is another vital aspect of your power choice. Work with a partner who has an extensive supplier network that is in tune with the current state of the market. While performance and pricing play a crucial role, time must also be considered and weighed in your determination. For example, AMPS is in constant communication with their supplier network to add this layer of information to the process.

A master energy plan that summarizes your up-front capital expenditure and long-term system performance is the key to your decision-making process. You will likely have multiple options to consider and need all variables properly captured. Developing a full picture of all options requires an understanding of analysis and system design, procurement, utilities, financing, and other items. Guiding this process is complex—you need a strong partner to summarize options and help drive the right solution. You need an apples-to-apples comparison to make an informed decision.

Production of alternative energy sources is financially attractive should you want to own and operate the equipment yourself. In many cases, extended warranties and user-friendly monitoring services help you understand system performance and keep the system operating at peak efficiency. Given the consistent production of alternative sources, outside investors are also interested in supporting your project and alternative power investment. To support this, the party receiving power agrees to buy at an established rate structure. These rates are typically better than those available from the utility provider and have defined escalations. The financier owns the system, operates, and maintains its performance. While the return on investment is not as attractive as a direct ownership scenario, it is an option to consider.

Federal, state, local governments, and utility companies encourage investing in efficient power producing systems. These incentives are generally in the form of tax benefits on the initial system investment and its depreciation. Additional incentives are available based on system performance. These need to be integrated into the financial model to give the full picture to help inform your decision-making process.

Monitoring production and tracking results is important to understand and validate your actual usage and performance. It also helps you understand the correlation between your energy needs, operations, and yields. It can help identify underperforming systems for planned maintenance and investigation before they can cause unplanned downtime or expensive damage. Knowing your actual operational performance offers the opportunity to guide decision making based on real data.

Solving the power needs of your facility can be complex. Understanding your operations and facility demands require expert engineering. Driving the optimal solution means an understanding of design, construction, supply chain, timing, operations, and monitoring. Choosing the right partner to lay the course toward the best solution from the beginning is key to a successful project. Holding control on the power decisions puts you in the driver’s seat to mitigate costs, carbon impact, and increase financial benefit.

Resource Innovation Institute is a non-profit organization committed to cultivating a better future for all of humanity. Their consortium of members brings perspectives from across the field—uniting architects and engineers, growers and operators, researchers, and analysts. Together, they measure, verify, and celebrate the world’s most efficient agricultural ideas. In this article, RII’s Technical Director and members of the organization’s 

 working groups share perspectives on ways growers can make the most of technical and financial support from 

Best Practices Guide on Automation & Controls for Cannabis Cultivation

 (4). Access RII’s free Best Practices guides and trainings at: 

https://catalog.resourceinnovation.org/item/controlled-environment-agriculture-market-transformation-strategy-implementation-plan-446270

https://catalog.resourceinnovation.org/item/program-design-market-engagement-primer-407538

https://catalog.resourceinnovation.org/item/best-practices-guide-automation-controls-cannabis-cultivation-435539

 leads sprint cycles and design reviews for the PowerScore resource benchmarking platform, performs analysis for Producer Resource Efficiency Plans, facilitates the Data Working Group of the Technical Advisory Council, manages the RII catalog, and supports live workshops. Azzaretti works with producers to visualize trends in facility Performance Snapshots and create case studies to celebrate excellence in environmental performance. Azzaretti represents RII on industry committees developing standards for CEA including the ASHRAE Technical Committee 2.2 (Plant and Animal Environments) and Task Group 1 of the UL 3600 Scorecard for Measuring and Reporting Circular Economy Aspects of Products, Sites and Organizations.

As Director of Engineering for ARCO/Murray Power Solutions group (AMPS), 

 leads an extensive in-house team of engineers and design/builders providing power solutions for clients. His team focuses on navigating and interrelating design, system performance, equipment supply-chain and lead times, utility rates, incentives, and monitoring to drive optimal solutions.

The Cultivation Classroom

Learn how having a firm understanding of how you plan to use your facility, what power options are available, and strong partners can guide you to the best solution which is critical to your bottom line.

Powering CEA: Power Supply Solutions for CEA Facilities

I recently had the pleasure of sitting down with our 2022 Cannabis Science Conference East Plenary Speaker, Dr. David “Dedi” Meiri. Dr. Meiri is an assistant professor at the Faculty of Biology at the Technion Israel Institute of Technology and a member of the Technion Integrated Cancer Center. Dr. Meiri heads the Laboratory of Cancer Biology and Cannabinoid Research at Technion, and is the founder of Cannasoul Ltd. In this interview, Dr. Meiri discusses his important work at Technion, challenges and opportunities in cannabis research, and a preview of his upcoming presentation for CSC East.

Can you tell us a little bit about the Technion Israel Institute and your work at the Laboratory of Cancer Biology and Cannabinoid Research?

: The Technion is the Technology Institute of Israel, a little bit like Massachusetts Institute of Technology (MIT) in the United States. At Technion we offer computer science and engineering, but also medicine and biology. Biology for many years was kind of like the stepson at Technion. But in 2005, the biology group won two Nobel prizes, so we have since become a very important faculty group, which I am part of. I’m part of the Technion Integrated Cancer Center (TICC). But in the last few years, my lab became more multidisciplinary when I started to work with cannabis. So, we are doing a lot with the plants and other indications on top of cancer.

Your talk at Cannabis Science Conference East is titled “Matching the Right Flower to the Right Bride.” What do you hope our audience will take away from this presentation, and can you share some of the key topics that you’ll be covering?

: People have used plants as a medicine for thousands of years. However, we are treating plants as a medicine very differently than how we treat traditional types of medicines. In plants, we are looking kind of at the whole plant, not even just cannabis. We’re seeing the same things with gingko, echinacea, and valerian as a whole. But what is valerian? There are many types and each one of them contain different compounds—the same is true for cannabis. Even more than that though, cannabis is affecting the endocannabinoid system in our body, every cell in our body is harboring the endocannabinoid. There are many receptors and cannabis has many active compounds—the cannabinoids—and it’s very wide.

Cannabis is actually effecting every cell in our body and every system, but what we need to determine is which type of cannabis will improve sleep, which will reduce pain, which will affect nausea, which will affect your mood, and so on. We don’t know enough yet.

Then we are going to more specific diseases such as epilepsy, Crohn’s, and colitis, and so on. We’re trying to be more and more specific. Again looking at which strain of cannabis or which type of cannabis. In my lab only, I have more than 1000 different types of cannabis, which one of them or which combination of molecules is effecting disease treatment.

For instance, a lot of people use cannabis and say it is improving their quality of life—a little bit improving sleep, a little bit reducing pain, and a little bit improving the mood, and altogether, you get something complete. Many types of cannabis can be effective. But when we’re starting to look at specific illnesses and somebody has insomnia, now I’m looking for a strain that’s improving sleep and for that, we try to match which cannabis or which compounds effect which disease. This is the major question in our field, and my lab is trying to close these gaps.

You’ve been a leader in cannabis research for many years now. What are some of the major differences you have seen while performing your research in Israel as opposed to other countries like the US that might be more restricted as far as cannabis laws?

: As a scientist in Israel, I have no restrictions at all. I need to have a license to do research and I need to renew this license every year, but it's very simple. And from that, I don’t have any restrictions. I can get cannabis from all the growers in Israel. I can do any type of science or research, and I think this is the major difference.

On top of that, 50 minutes from here, I have Raphael Mechoulam, who was the godfather of this field. He defined the cannabinoids in 1964 and 1965. And for that, he did a huge amount of research. He is 92 this year, but still he’s working and still active, and I have the privilege to be quite close to him, and to learn a lot of the methods and the things that he did.

There are few people in Israel that are worthy students and work on that, so the group and the support of each other is big. But also, Mechoulam was always an important scientist in Israel. He wasn’t a scientist that nobody paid attention to. He actually was the dean and director for Jerusalem University, which is the biggest in Israel, so he wasn’t just another scientist.

This has also opened things up for the government, healthcare, and people for this field. It wasn’t as a scientist. I’m not talking about the recreational side. I’m talking about the science side, and the health side of cannabis. I think because of Mechoulam, it was very easy for us to step in.

Do you find yourself in situations where you’re able to work with researchers that could add value, but they might be based in the US and are not able to conduct research here? Do you ever have situations where you’re able to kind of cross borders and collaborate?

: I think this is the major obstacle or barrier. It’s very difficult to work with scientists abroad. I have many friends in the US and Canada that are working in similar research areas, but transferring material has always been an obstacle.

However, within the last three years, Israel has started to allow the export and import of cannabis. So in that respect, it has become easier. So let’s say in Australia for example, I have collaborators that we send materials to and we receive materials and goods from Canada. In the US, it’s still very, very strict. And even though I have a lot of friendsin the US—including some big names such as Ethan Russo and Dr. John Abrams, among others—it’s still limited to just sharing data and knowledge. We cannot really work on the same projects together.

Another hurdle is that we can’t apply for funding together, which is what I can usually do in other types of research. If we can’t transfer materials then we can’t work on the same thing, so this is a huge obstacle still with the US. People often ask me what will create a big change or when will there be an increase in the data, I think when the US becomes more open regarding the science we will see change. When they allow scientists to work in freedom and to collaborate in other countries, that will be the difference.

I can say that the Technion is very important and it’s like MIT, but it’s not the same as MIT. The big institutes and the leading institutes in research in the world are still in the US in terms of budget and smart people. I think allowing free research in the US will be the change. So, we are waiting for you guys!

What is the legality of cannabis in Israel? Is it just legal for medical use? Is it legal for adult use? What does the landscape look like there?

: It’s legal just as for medical use. It’s actually under our healthcare system. The big difference in Israel compared to other countries is that since 2007 cannabis has been under healthcare, and healthcare in Israel is universal. Medical insurance is compulsory, so we are paying for our healthcare, but it’s deductible from our salary. Every citizen—it doesn’t matter if you work or not work—must have government insurance. When we go to a physician or get medicines, we are not paying for that. It’s already been covered—and that includes cannabis. Actually, patients in Israel get a prescription for cannabis and buy it in the pharmacy under a prescription with their healthcare that is subsidized. The cost is low. We have 115,000—almost 120,000—patients that are getting cannabis. It’s the most prescribed medicine in Israel.

So, if you think that the population is around seven or eight million people, so you understand as a percentage that it’s a huge population of patients that are getting medical cannabis, and this is also changing the stigma. For instance, if your grandma is getting cannabis because she has cancer, or your nephew that has epilepsy is getting cannabis, and the autistic kids that you see are getting cannabis—you don’t think any more about that as a drug or just for a stoner—sorry for using that terminology, but medical use has made cannabis become more acceptable.

So, if you see somebody in Israel using cannabis, people will likely think “They probably have PTSD, Crohn’s, or colitis,” or something like that. The concept is totally different here.

Five or six years ago when I started to work in cannabis, I would give talks in hospitals at least once a week. I think at this point, there are no hospitals or even departments in hospitals that I didn’t share my results with. So at that time when I would share my data, physicians would say things like “Over my dead body, that we will prescribe cannabis.” Well . . . there should be a lot of dead bodies in Israel today because they are all prescribing cannabis now. But, you don’t hear comments like that anymore. There is no department, there is no physician in Israel that’s not thinking about it as a medicine and prescribing it if their patient needs it, and this is a huge change of concept.

You have been a longtime friend of the Cannabis Science Conference, what is your favorite thing about the show and what keeps you coming back?

: It’s a tricky question to answer because you are asking it. It would be easier for me to answer to somebody else because it would look more reliable. But honestly, it’s the best conference that I participate in. (And again, it’s not because you’re asking me.) You can see me saying this at other conferences. I think there is only one that I consider similar, and it’s in Australia.

But literally, Cannabis Science Conference is a big show with a lot of good science. The major people in the industry come, but there is also a mixture of industry science physicians that are really coming to learn. There are a lot of conferences like that also in Israel, but I don't think they succeed to reach the point, which is the top-notch people coming and collaborating together.

I also learn a lot at these conferences. I participate in a lot of conferences, but I am not learning a lot from them. But there are few cherries, like yours, that are always fun, but also I’m coming back with knowledge, partners, collaborations, and ideas. It’s just so important for science and for moving forward. I think it’s extremely important.

This interview has been edited for length and clarity. For more with Dr. Meiri please visit: 

https://www.cannabissciencetech.com/view/dr-dedi-meiri-on-plant-medicine-matching-the-right-flower-to-the-right-bride

 is the columnist and editor of “Cannabis Crossroads” and a contributing editor to 

 magazine. Crossney is also the founder of Cannabis Science Conference and now serves as Director of Cannabis Events at MJH Life SciencesTM. Direct correspondence to: 

Cannabis Crossroads

In this interview, Dr. David “Dedi” Meiri discusses his important work at Technion, challenges and opportunities in cannabis research, and a preview of his upcoming presentation for CSC East.

2022 CSC East Plenary Speaker Highlight: Dr. Dedi Meiri

Light intensity, direction, photoperiod, and spectral composition play essential roles in the growth and phytochemical expression of all photosynthetic plants. In the work presented here, we evaluated the effects of variable red-light exposure on the phytochemical content of four Group III cannabis (cannabidiol- and cannabigerol-dominant) cultivars. In the presence of full-spectrum light emitting diodes, the modulation of red-light frequencies affected the expression of various major and minor cannabinoids, various terpenes, and six anthocyanins. The plants treated with daily on/off cycles of red-light yielded higher average concentrations of total cannabinoids and anthocyanins, but a lower mass of trimmed flower material, compared to control plants exposed to 1000 W full-spectrum-light. These findings represent preliminary efforts to characterize the phytochemical effects of light modulation in Group III cannabis cultivars. Additionally, this study is the first to characterize terpene expression and volatilization in real time using mobile gas chromatography and reports variable anthocyanin expression in cannabidiol- and cannabigerol-dominant cannabis cultivars.

Light intensity and spectrum play pivotal roles in the growth and development of all plants. Photosynthesis, photorespiration, germination, photoperiodic control of flowering, phototropism, and entrainment of circadian rhythms are physiological mechanisms that are all dependent on light for optimal plant growth (1). The efficacy of horticultural lighting can be distilled down to three primary variables: color of the light (frequency), light coverage of the crop, and using adequate power (photon density) to achieve desired yields. McCree (2) examined 22 crop plants and determined their average photon utilization across the frequency spectrum of sunlight. He used these data to produce a graph, known as the McCree Curve, which illustrates how plants utilize light, from ultraviolet and blue short wavelengths through the longer wavelengths of red and far-red light (2). McCree elucidated the effect of blue light (400-500 nm) on facilitating vegetative growth, and further elucidated the effect of yellow, amber, and red light (620-780 nm) in the flowering stages (3). More specifically, blue light affects nuclear receptors that regulate light-dependent growth responses, such as the inhibition of hypocotyl elongation, leaf expansion, stem growth, and phototropism (4-9). Phytochrome and phototropins, principally red (R) and far-red (FR) (600-800 nm) as well as blue (B) (400-500 nm), act through phytochrome and cryptochrome signaling pathways to regulate photomorphogenic and photoperiodic responses (10,11). Phototropins regulate light-dependent movement, a process known as 

Other investigators have used the McCree Curve as the basis for investigating the effects of manipulating light to enhance growth (12). Early work focused on food plants using metal halide (MH) and high-pressure sodium (HPS) lighting. MH fixtures produce light predominantly in the blue frequencies, whereas HPS lights produce primarily amber and red frequencies. These technologies have been used as the standards in horticultural lighting and continue to be used today. Early light-emitting diodes (LEDs) replicated MH and HPS with diodes that were biphasic and gave sharp peaks of light in the blue and red frequencies, as opposed to a broad spectrum of colors across the photosynthetic range (13). These biphasic LEDs have been supplanted by full-spectrum LEDs that emulate the McCree Curve and the spectrum of natural sunlight.

The effects of light used to grow food and herb plants have been extensively investigated, especially regarding the manipulation of the light spectrum to enhance growth. This research has documented the effects of light spectrum manipulation on vegetative growth and, more recently, the effects of light manipulation during flower and seed production of vegetables and fruits. Photomorphogenic mutants are excellent tools for studying the interactions between light and plant development. 

 refers to how plants modulate their development in response to light. Several sets of genes are responsible: 1. photoreceptor genes; 2. early signaling intermediates; 3. pleiotropic genes; and 4. downstream effectors (14). For example, monogenic recessive mutations for the elevated expression of pigment elements (hp-1, hp-1w, hp-2, hp-2j, hp-2dg) have been described in tomato (

) (15). These mutations cause exaggerated light responsiveness, shortened hypocotyls, elevated anthocyanin content, delayed development, darker pigmentation of leaves and fruits, and later onset of fruit ripening, as compared to isogenic wild type tomatoes. These hp mutants also overproduce several flavonoids, as increased pigmentation was found to be attributable to increased concentrations of chlorophyll in unripened fruits and carotenoids in mature red fruits (16,17). Furthermore, discovery of the det1 and ddb1 mutants led to the coupling of photomorphogenesis and over production of phytonutrients (18). Lastly, the modulation of light signaling to increase the functional quality of fruits was demonstrated by increased synthesis of flavonoids in tomatoes carrying the hp mutation (13,19). This link led to the hypothesis that manipulation of light signaling machinery may be a means of affecting the functional properties in the tomato fruit and other plants and fruits (15). Light signaling genes are highly conserved in the plant kingdom, and it is highly likely that their effects are reproducible in other plant species either closely or distantly related to tomatoes (20). Therefore, we have used these studies as a template to evaluate the effects of variable red-light exposure on phytochemical content in Group III cannabis, (that is, cannabidiol [CBD]- and cannabigerol [CBG]-dominant) cultivars.

The results presented here do not provide the technical resolution to assess the effects of variable light spectra on individual gene expression, such as individual phytochrome receptors, because of the federal restrictions of working with cannabis in a traditional academic research setting. However, these findings provide insight into some of the phytochemical responses to differential light treatments in four Group III cannabis cultivars. Initial studies of the effects of light manipulation of cannabis have focused almost exclusively on increasing the tetrahydrocannabinol (THC) content in Group I flower material (THC-dominant) (21). More recent investigations have focused on enhancing the production of CBD and terpenes (22). These early efforts have focused primarily on the vegetative phase of plant growth. This is because physical growth metrics of interest, such as internodal distance, are easily measured and replicated. In a complimentary fashion, the work presented here focuses on evaluating the effects of light manipulation on the expression of several types of secondary metabolites produced by Group III cannabis cultivars, such as major and minor cannabinoids, various classes of terpenes, and the anthocyanin flavonoids.

Group III Cannabis Cultivars and Horticultural Lighting Conditions

In this study, we exposed four different Group III cannabis cultivars to four different lighting conditions during their flowering cycles in individual cultivation tents. The cultivars were produced by ZED Therapeutics and included White Tahoe Cookies x Purple Punch (B73), Blackstar Sherbet (B246), Gatorade Purple Punch (B120), and the CBG-dominant strain CBG127 (B127). Control plants were grown in Tents 1 and 2 under a 1000 W full-spectrum Harvester LED 12 h on/12 h off, and a 600 W full spectrum Harvester LED 12 h on/12 h off, respectively (Curtis Mathes Grow Lights). Experimental plants were grown in Tents 3 and 4 under 600 W white 12 h on/12 h off + 400 W red and far-red 4 h on/4 h off/4 h on/12 h off (slow red cycling), and 600 W white 12 h on/12 h off + 400 W red and far-red 2 h on/1 h off/2 h on/1 h off/2 h on/1 h off/3 h on/12 h off (rapid red cycling), respectively. The lights were positioned approximately 24-in. off the canopy in all four tents to ensure that any differences in photosynthetically active radiation (PAR) were solely attributable to differences in wattage or spectrum (see 

). All plants were grown from clones in custom organic soil from Lane Forest Products (Eugene, Oregon). All plants were watered and fed uniformly across the four different cultivars and lighting conditions, respectively. The water was obtained by reverse osmosis filtration and the nutrients Build a Bloom (Build A Soil) and AGmino, a water soluble, nitrogen fertilizer (14-0-0) (Down to Earth) prepared to final concentrations of 700–900 ppm with a pH between 6.2–6.8, were applied every third day.

Chlorophyll Content Index (CCI) values were quantified as a surrogate measurement for chlorophyll content (µmol m

) (23), using an MC-100 chlorophyll content meter by Apogee Instruments. Measurements were taken in triplicate on multiple leaf sites of each plant daily.

Terpene expression and volatilization was analyzed in situ using the NovaTest P300 portable gas chromatograph (GC) by Nanova Environmental. The P300 uses a microfluidic photoionization detector (uPID), which detects more than 400 volatile organic compounds (VOC) including terpenes at the parts-per-billion (ppb) concentration in air. The air was sampled at a rate of 10 mL/min using polytetrafluoroethylene (PTFE) inlet tubing, which was placed inside the cultivation tents during sampling. Sampling was performed on a daily basis during the same time interval. The instrument was calibrated for 19 cannabis-based terpenes (see 

As described previously (24), samples were collected at predetermined times and were analyzed by high performance liquid chromatography (HPLC) methods developed by ZED Therapeutics. Briefly, dried samples were treated with methanol and syringe filtered, prior to separation on a C18 (75 mm x 3.0 mm x 2.2 µm) column and an acetonitrile gradient using Shimadzu’s Cannabis/Hemp Analyzer. Certified reference standards from Cerilliant were used to identify and quantify cannabidivarinic acid (CBDVA), cannabidivarin (CBDV), cannabidiolic acid (CBDA), cannabigerolic acid (CBGA), CBG, CBD, tetrahydrocannabivarin (THCV), tetrahydrocannabivarinic acid (THCVA), cannabinol (CBN), ∆

-THC), cannabicyclol (CBL), cannabichromene (CBC), tetrahydrocannabinolic acid (THCA), and cannabichromenic acid (CBCA). Calibration was performed using a set of five serial dilutions of each reference standard (2.5, 12.5, 25.0, 125.0, and 250.0 µg/L) with a linearity greater than 0.998. The limits of detection and quantitation were determined experimentally to be 0.5 and 1.0 µg/L, respectively.

A detailed methodology of the anthocyanin analysis performed in this study will be reported elsewhere (30). Briefly, dried flower samples were milled using a Retsch CryoMill. The precooling time was set to auto, followed by two cycles of 1-min milling time at a frequency of 25 Hz. Between cycles the system was set for a 1-min intermediate cooling at 5 Hz. Batches of 100 mg of milled hemp inflorescence were loaded into a 1.7 mL microcentrifuge tube. Next, 1 mL of extract solvent was added to the microcentrifuge tube. The extraction solvent consisted of a 70:30:1 mix of methanol, water, and trifluoracetic acid (TFA), respectively. Samples were vortexed until the milled hemp was suspended uniformly, then sonicated for 25 min. Next, the samples were centrifuged for 20 min at 4000xg. The extract was separated from the solid and added dropwise to 5 mL of hexane in a 3-dram glass vial. The extraction process was repeated a second time and the extract was added to the extract–hexane vial. The extract–hexane vial was then sonicated for 30 min and stored at 4 °C overnight. The lower aqueous layer was removed using a pipette. At the hexane–extract solvent interface, there was usually a small quantity of precipitate that was not collected. The aqueous layer was diluted 1:3 with 30:70:1, methanol, water, and TFA, respectively, to a final volume of 1 mL. Solutions were filtrated with a 13 mm nylon 0.2 µm pore size syringe filter. Finally, filtrate solutions were cleaned using solid-phase extraction (SPE) (Waters Oasis Prime HLB 1 cc/30 mg cartridges) and pipetted into liquid chromatography (LC) vials. A Shimadzu LCMS-8040 triple quadrupole instrument equipped with LC-20AD solvent delivery pumps, DGC-20A5 degassing unit, SIL 20AC XR autosampler, CTO 200AC column oven, and CBM-20A system controller was used for the targeted analysis. Instrument control and data acquisition were performed using LabSolutions software v.5.97 (Shimadzu Corp.). Injections of 1 µL were used. Separation was achieved using a Restek Raptor C18 (100 mm x 2.1 mm x 2.7 µm). Mobile phases consisted of water with 0.1% formic acid (solvent A) and acetonitrile with 0.1% formic acid (solvent B). Gradient elution was performed at a flow rate of 0.35 mL/min, at 5% B from 0–2 min, then a ramp to 95% B from 2–16 min with a hold at 95% B from 16–18 min. Re-equilibration to 5% B was performed from 18–21 min. The temperature of the autosampler tray and the oven were set at 10 °C and 50 °C, respectively. Electrospray ionization (ESI) was performed in positive mode. The mass spectrometry (MS) data was collected under the following ESI conditions: nitrogen nebulizing gas and drying gas flows were 3 L/min and 10 L/min, respectively; the desolvation line temperature was 250 °C and the heat block temperature was 400 °C; and the interface voltage was 4.5 kV. Each analyte was monitored by optimized multiple reaction monitoring (MRM) transitions (see Table I).

Unpaired Mann-Whitney analyses were performed using the Prism software suite by GraphPad, assuming non-Gaussian distribution. Similarly, grouped analyses were performed using a two-way ANOVA. The symbols *, **, ***, **** were used to represent p-values less than 0.05, 0.005, 0.001, and 0.0001, respectively. The “ns” is representative of p-values greater than 0.05.

Chlorophyll content was measured under the four different lighting conditions as an indicator of plant metabolism. For example, depleted or rapidly depleting chlorophyll content in the leaves can be indicative of nutrient deficiencies. All plants were provided the same amount of nutrients, which should be revised in subsequent experiments to an “as needed” basis that is predicated on consistent nutrient levels in the watering flowthrough to account for differences in metabolic demand that are triggered by differences in light intensity. For example, the greatest differences in chlorophyll content during the flowering cycle were observed between the 1000 W and 600 W control tents (tents 1 and 2, p-values <0.0001 in three of the four cultivars). This relative depletion of chlorophyll content is likely attributable to insufficient nutrient feeding (see 

). Conversely, there were no differences in CCI across the time course in tent 3 compared to tent 4 for all four cultivars. Interestingly, Gatorade Purple Punch demonstrated the most consistent rate of chlorophyll depletion over time, as evidenced by the lowest variability between the four different lighting conditions (Figure 2). Conversely, Blackstar Sherbet demonstrated the most variability and expressed the highest amounts of anthocyanins (see section titled “Anthocyanin Expression”), which collectively could be an indicator that this cultivar is the most sensitive or responsive to changes in light intensity and spectrum.

Volatilized terpenes in the cultivation tents were determined via mobile gas chromatography (GC), a potentially disruptive technology that can provide considerable insight about terpene expression in real time without having to harvest plant material for analysis. Up to seven terpenes were detected on any single day (

) and 13 of the 19 detectable terpenes were detected at least once during the experimental period in the control (tent 1–1000 W full-spectrum LED). Linalool, isopulegol, and β-caryophyllene were detected more often than other terpenes. Furthermore, the highest total terpene concentrations were 1308 ppb (eucalyptol 608, y-terpinene 219, and geraniol 473 ppb) and were detected in Tent 1. Comparably, one to five different terpenes were detected simultaneously in Tents 2-4, with α-pinene, limonene, and linalool being detected more often than others. Interestingly, the largest spikes in individual terpene expression were attributed to isopulegol (1010 ppb, Tent 2) and geraniol (1291 ppb, Tent 2), a consistent feature across all four lighting conditions (

). Additionally, notable spikes in linalool and D-limonene were observed from Tents 3 and 4 (Figure 4). As expected, terpene expression increased at later times; however, the total quantities of terpenes did not differ between each of the four different lighting conditions (Figure 4, p-values >0.05). These results suggest that changes in photosynthetic photon dosage (light intensity in the photosynthetic range) and spectrum can alter the terpene profile, but that these changes do not necessarily affect the total amounts of terpenes produced. The cellular mechanisms responsible for the differences in the terpene profiles remain to be determined. However, the notably more diverse terpene profile observed in Tent 1 may suggest that the cumulative effect of enhanced light exposure could be an antagonistic stressor that induces enhanced terpene expression, even during a period of potential nutrient deficiency.

Considerable variability was observed in the expression profiles of the primary acidic cannabinoids (CBDA, CBGA, THCA, and CBCA) between the four different cultivars (

). Interestingly, WTC x PP was the only cultivar that produced detectable amounts of CBDVA (Tents 3 and 4) (see 

). Also, CBCA was undetectable in the CBG127 grown in tents 2 and 3. The highest amounts of total cannabinoids, CBDA, and CBGA, were produced in Tents 2 and 4, albeit the overall difference was not significant amongst the four different lighting conditions (see 

, p=0.827). The most total dry plant material was collected from Tent 3, with the least amount being collected from Tent 2 (p=0.114). Similarly, the most amount of trimmed flower material was also collected from Tent 3, with the least being produced in Tent 2 (p=0.029). Interestingly, Tent 1 produced 0.11 g/W compared to 0.13 g/W in Tent 2. These results provide further support for the hypothesis that the plants under the 1000 W full-spectrum control light were underfed relative to the plants under the three other lighting conditions, as one would generally expect higher a g/W yield under the higher wattage light when fed adequately.

Anthocyanins are a subclass of the flavonoid family of compounds that are starting to attract attention in the cannabis and hemp industries for their medicinal properties. Anthocyanins have an anthocyanidin core structure bound to various 3- and 5-linked glycosides. Besides the variable pH-sensitive pigmentation they confer on many natural products, anthocyanins have been reported to exhibit antioxidant properties (25). Numerous anthocyanins glycosides were detected (30); however, only six prominent compounds, comprised of four different anthocyanidins, were pseudo-quantifiable (

). These included cyanidin-rutinoside, a predominantly reddish-purple pigment, which has been shown to be a potent sirtuin 6 (SIRT6) activator (26), as well as being involved in telomere maintenance and multiple molecular pathways related to aging. Peonidin-rutinoside was also detected, which is purplish-red, and has been shown to be an inhibitor of human metastatic breast cancer cells (27). Two different delphinidin-rutinoside isomers were detected. Delphinidin is a pH-sensitive antioxidant that is blue in acidic pH and red in basic pH (28). Lastly, two different pelargonidins were detected (diglucoside and rutinoside), which are orange pigments with antioxidant activity (29).

The highest total anthocyanin concentrations were found in Gatorade PP and Blackstar Sherbet, with cyanidin-rutinoside and peonidin-rutinoside being the most abundant compounds. Conversely, substantially lower concentrations were found in CBG127 and WTC x PP. Remarkably, CBG127 was devoid of detectable delphinidin-rutinoside 1, delphinidin-rutinoside 2, and pelargonidin-diglucoside under all four lighting conditions; pelargonidin-rutinoside was only detectable in the plant grown in Tent 2. Similarly, WTC x PP was devoid of pelargonidin-diglucoside under all lighting conditions and delphinidin-rutinoside 1 was only detected in plants grown in Tents 2 and 4. Collectively, the highest total anthocyanin concentrations were detected in Tents 2 and 4, suggesting that a lower photosynthetic photon dosage or a more abundant exposure of red-light wavelengths—albeit intermittent—are favorable for increasing anthocyanin expression (

). However, the dramatic differences in anthocyanin expression between the four different Group III cannabis cultivars presented here, particularly between Blackstar Sherbet and CBG127, appears to suggest that anthocyanin expression is primarily driven by genetic factors (p=0.0004) as opposed to environmental factors (p=0.0916).

Collectively, these results suggest that polyhybrid cultivars of Group III cannabis are highly responsive to different lighting regimens and that phytochemical content can be affected by the modulation of light intensity and different red-light frequencies. Additional research is required to investigate this phenomenon at the genetic and epigenetic levels. Additionally, these data suggest that Group III cannabis cultivars allocate finite amounts of cellular resources to the production of flower material (yield) or the various classes of phytochemicals. This allocation may represent a balance between the major phytochemical classes. For example, Blackstar Sherbet produces relatively higher amounts of anthocyanins but notably lower amounts of cannabinoids, compared to the other three cultivars in this study (see Table II). This interplay is likely influenced by genetic factors; however, the cellular allocation of resources toward different subclasses of phytochemical compounds has also now been shown to be altered by lighting intensity and spectrum.

Figure s1 and Tables sI-sIII were not included in the print version of this article. These graphics are considered supplemental information to the published article version.

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Peer-Reviewed Article

In the work presented here, the authors evaluated the effects of variable red-light exposure on the phytochemical content of four Group III cannabis cultivars.

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Variable Red Light Exposure Affects Phytochemical Content in Group III Cannabis Cultivars